I was just reading the paper in the title (pdf), which Alexei Efros talked about at CVML. It's from this years ICCV.
The basic idea of the paper is to do object detection by training a linear SVM on hog features for each positive example. I thought the idea was pretty cool and wanted to write something about it... and then I saw there is already a post by the first author, Tomasz Malisiewicz, in his own blog.
He also discusses some of his (matlab :( ) code for non-maximum suppression.
So check out his blog for more details on this cool paper :)